(Click di piksha wey dey above to watch video for dis lesson)
Welcome to di Model Context Protocol (MCP) Workshop! Dis kain hands-on workshop combine two top latest technologies wey go change how person dey build AI application dem:
- 🔗 Model Context Protocol (MCP): One open standard for easy AI-tool work together
- 🛠️ AI Toolkit for Visual Studio Code (AITK): Microsoft strong AI development extension
By di time you don finish dis workshop, you go sabi how to build smart applications wey fit join AI models with real-world tools and services. From automated testing reach custom API integrations, you go get skills to fit solve serious business wahala.
MCP na di "USB-C for AI" - na universal standard wey dey connect AI models to other tools and data sources.
✨ Main Features:
- 🔄 Standardized Integration: Universal interface to join AI-tool together
- 🏛️ Flexible Architecture: Local and remote servers wey dey use stdio/SSE transport
- 🧰 Rich Ecosystem: Tools, prompts, and resources inside one protocol
- 🔒 Enterprise-Ready: Security and reliability inside
🎯 Why MCP Matter: Just like USB-C stop cable wahala, MCP stop the trouble of AI integration. One protocol, plenty possibilities.
Microsoft AI development extension wey fit turn VS Code into AI powerhouse.
🚀 Core Bana:
- 📦 Model Catalog: Access models from Azure AI, GitHub, Hugging Face, Ollama
- ⚡ Local Inference: ONNX-optimized CPU/GPU/NPU running
- 🏗️ Agent Builder: Visual AI agent development with MCP connection
- 🎭 Multi-Modal: Text, vision, and structured output support
💡 Development Benefits:
- No wahala model deployment
- Visual prompt engineering
- Real-time testing playground
- Smooth MCP server join
Duration: 15 minutes
- 🛠️ Install and configure AI Toolkit for VS Code
- 🗂️ Check out Model Catalog (100+ models from GitHub, ONNX, OpenAI, Anthropic, Google)
- 🎮 Master di Interactive Playground for real-time model testing
- 🤖 Build your first AI agent with Agent Builder
- 📊 Check model performance with built-in metrics (F1, relevance, similarity, coherence)
- ⚡ Learn batch processing and multi-modal support skill dem
🎯 Learning Outcome: Build proper AI agent with full understanding of AITK functions
Duration: 20 minutes
- 🧠 Understand Model Context Protocol (MCP) architecture and ideas
- 🌐 Explore Microsoft MCP server setup
- 🤖 Build browser automation agent using Playwright MCP server
- 🔧 Join MCP servers with AI Toolkit Agent Builder
- 📊 Configure and test MCP tools inside your agents
- 🚀 Export and deploy MCP-powered agents for production
🎯 Learning Outcome: Deploy AI agent wey dey powered by external tools through MCP
Duration: 20 minutes
- 💻 Build custom MCP servers using AI Toolkit
- 🐍 Configure and use latest MCP Python SDK (v1.9.3)
- 🔍 Setup and use MCP Inspector for debugging
- 🛠️ Build Weather MCP Server with professional debugging workflow
- 🧪 Debug MCP servers for both Agent Builder and Inspector environment
🎯 Learning Outcome: Develop and debug custom MCP servers with modern tools
Duration: 30 minutes
- 🏗️ Build real-world GitHub Clone MCP Server for development workflow
- 🔄 Implement smart repository cloning with validation and error handling
- 📁 Create intelligent directory management and VS Code integration
- 🤖 Use GitHub Copilot Agent Mode with custom MCP tools
- 🛡️ Apply production-ready reliability and cross-platform compatibility
🎯 Learning Outcome: Deploy production-ready MCP server wey go simplify real development workflow
Change your development workflow with smart automation:
- Smart Repository Management: AI-powered code review and merge decisions
- Intelligent CI/CD: Automated pipeline improvement based on code changes
- Issue Triage: Automatic bug classification and assignment
Improve testing with AI automation:
- Smart Test Generation: Automatically create full test suites
- Visual Regression Testing: AI-powered UI change detection
- Performance Monitoring: Early issue detection and fixing
Build smarter data processing workflow:
- Adaptive ETL Processes: Self-optimizing data transformation
- Anomaly Detection: Real-time data quality checking
- Smart Routing: Smart data flow management
Make top customer interaction:
- Context-Aware Support: AI agents get access to customer history
- Proactive Issue Solution: Predict customer service issues
- Multi-Channel Integration: Unified AI experience across different platforms
| Component | Requirement | Notes |
|---|---|---|
| Operating System | Windows 10+, macOS 10.15+, Linux | Any modern OS |
| Visual Studio Code | Latest stable version | Needed for AITK |
| Node.js | v18.0+ and npm | For MCP server development |
| Python | 3.10+ | Optional for Python MCP servers |
| Memory | 8GB RAM minimum | 16GB recommended for local models |
- AI Toolkit (ms-windows-ai-studio.windows-ai-studio)
- Python (ms-python.python)
- Python Debugger (ms-python.debugpy)
- GitHub Copilot (GitHub.copilot) - Optional but useful
- uv: Modern Python package manager
- MCP Inspector: Visual debugging tool for MCP servers
- Playwright: For web automation examples
After you finish dis workshop, you go fit master:
- MCP Protocol Mastery: Understand architecture and implementation patterns well well
- AITK Proficiency: Expert in AI Toolkit for quick development
- Custom Server Development: Build, deploy, and maintain production MCP servers
- Tool Integration Excellence: Join AI with existing development workflow smoothly
- Problem-Solving Application: Use learned skills to handle real business issues
- Setup and configure AI Toolkit in VS Code
- Design and build custom MCP servers
- Join GitHub Models with MCP architecture
- Build automated testing workflow with Playwright
- Deploy AI agents for production
- Debug and improve MCP server performance
- Build enterprise-scale AI integrations
- Use good security practice for AI apps
- Design scalable MCP server architectures
- Build custom tool chains for specific areas
- Mentor others in AI-native development
- MCP Specification (2025-11-25)
- AI Toolkit GitHub Repository
- Sample MCP Servers Collection
- Best Practices Guide
- OWASP MCP Top 10 - Security best practices
🚀 Ready to change your AI development workflow?
Make we build future intelligent applications together with MCP and AI Toolkit!
Continue to: Module 11: MCP Server Hands-On Labs
Disclaimer: Dis document don translate wit AI translation service Co-op Translator. Even though we dey try make am correct, abeg sabi sey automated translations fit get error or wahala. Di original document wey e dey for im own language na di correct tin. If na important information, e good make person get professional human translation. We no go take responsibility for any misunderstanding or wrong meaning wey fit show because of dis translation.